Thông tin cơ bản
Tiến sỹ Võ Sỹ Nam là Giám đốc Trung tâm Tin Y Sinh, Viện Nghiên cứu Dữ liệu lớn Vingroup (VinBigdata) và là Giảng viên liên kết tại Viện Kỹ thuật và Khoa học Máy tính, VinUniversity. Trước khi gia nhập VinBigdata, Tiến sỹ Nam là nhà nghiên cứu Tin sinh học Cấp cao tại Trung tâm Khoa học Dữ liệu, Đại học Chicago. Ông làm nghiên cứu sau tiến sỹ về Sinh học Tính toán tại Trung tâm Ung thư MD Anderson, Đại học Texas sau khi lấy bằng Tiến sĩ Khoa học Máy tính tại Đại học Memphis, Mỹ.
Các lĩnh vực nghiên cứu của Tiến sĩ Nam tập trung vào phân tích và diễn giải dữ liệu multi-omics quy mô lớn nhằm nghiên cứu nguy cơ bệnh và phản ứng có hại của thuốc. Các phương pháp của anh đã được áp dụng cho một số bộ dữ liệu lớn nhất thế giới bao gồm Bản đồ hệ gen ung thư (TCGA) và Nghiên cứu ứng dụng điều trị để tạo ra các liệu pháp hiệu quả (TARGET). Ông hiện đang chủ trì một số dự án giải trình tự và phân tích hệ gen trên quần thể người Việt nhằm nghiên cứu các bệnh phức tạp ở Việt Nam.
- Bioinformatics, with an emphasis on multi-omics data analysis.
- Data Science/Machine Learning, with an emphasis on biomedical data analysis.
- High Performance Computing, with an emphasis on cloud computing and workflow acceleration.
Director, Center for Biomedical Informatics, Vingroup Big Data Institute, Vietnam. 2019- present
- 1000 Vietnamese Genomes Project, Adverse Drug Reactions, Antimicrobial Resistant.
- Management, Analysis, Sharing, and Harmonization of Big Biomedical Data.
- Analysis and interpretation of short/long-read sequencing data from WGS/WES.
Senior Bioinformatician, Center for Translational Data Science, The University of Chicago, USA. 2017-2019
- Workflows for Somatic Variant Calling, Structural Variant Detection, Variant Annotation.
- Analysis and interpretation of short-read sequencing data from gene panels/WES/WGS.
- Workflow analysis for large-scale biomedical data.
Postdoctoral Fellow, MD Anderson Cancer Center, The University of Texas, USA. 2016-2017
- Computational methods for HLA Typing, TCR Profiling, Neo-antigen Prediction.
- Analysis and interpretation of WGS/WES, mass spectrometry data (MS).
Research Assistant, Department of Computer Science, The University of Memphis, USA. 2009-2016
- Computational methods for Sequence Alignment, Variant Calling, Gene Expression Analysis.
- Analysis and interpretation of WGS, microarray data.
Affiliate Assistant Professor, College of Engineering and Computer Science, VinUni, Vietnam. 2020-present
Teaching Assistant, Department of Computer Science, The University of Memphis, USA. 2009-2013
- Undergraduate courses: Data Structures, Design and Analysis of Algorithms, Foundations of Computing.
- Graduate courses: Bioinformatics Algorithms, Advanced Topics in Algorithms, Data Mining.
Lecturer, Department of Systems Engineering, National University of Civil Engineering, Vietnam. 2005-2009
- Undergraduate courses: Introduction to Computer Science, C/C++ Programming Languages; Networks Application Programming with Java.
Awards and Honors
- Best paper award, IEEE KSE conference, Vietnam. 2019
- Best paper runner up award, MCBIOS conference, USA. 2014
- Honor for student research advising, National University of Civil Engineering, Vietnam. 2006-2008
- Scholarship for excellent students, Hanoi University of Technology, Vietnam. 2000-2004
- Third prize in the National Olympiad in Mathematics for K12 students, Vietnam. 1999
- Fourth prize in the Mathematical Problem-Solving Competition for high-school students, Journal of Mathematics and Youth, Vietnam Mathematical Society, Vietnam. 1999
- Fourth prize in the National Olympiad in Mathematics for K9 students, Vietnam. 1996
- Top prizes in Hatinh Province Olympiad in Mathematics and Physics, Vietnam. 1996-1999
Ph.D., Computer Science, The University of Memphis, USA. 2016
Dissertation: Computational Methods for Gene Expression and Genomic Sequence Analysis.
M.S., Bioinformatics, The University of Memphis, USA. 2011
Thesis: Analysis of Microarray Data with Directed Graphs.
M.S., Computer Science, Hanoi University of Science and Technology, Vietnam. 2007
Thesis: XML Schema Automatic Matching.
B.S., Computer Science, Hanoi University of Science and Technology, Vietnam. 2004
Project: Normalization of Relational Database Schemas.
- MASH (closed source platform): Management, Analysis, Sharing, and Harmonization of Big Biomedical Data.
- VASpark: Variant Accelaration using Spark.
- ClinAnnot (closed source tool): Clinical Annotation of Genomic Variants.
- pMHCb: Neo-antigen prediction using MS data.
- IVC: Variant calling using WGS data.
- RandAL: Short-read alignment using WGS data.
- mDAG: Gene expression pattern prediction using microarray data.
- VINIF.2020.DA02. Vietnamese Genome-based Prediction of Disease Risks (VGP). Multiple Principal Investigator. (2020-2023)
- VINIF.2019.DA109. Fighting antibiotic-resistant pathogenic bacteria using genomics sequencing and big data analytics. Senior member. (2019-2022)
- CPRIT-IIRACB RP180248. Characterizing cancer genome instability and translational impact using new sequencing technologies. Grant writer. (2018-2021)
- NSF-CCF 1320297. Analysis of gene expression data using transitive directed graphs. Grant writer and key researcher. (2013-2016)
- With SEAPharm network. Prevalence of pharmacogenomic variants in 100 pharmacogenes among Southeast Asian populations under the collaboration of the Southeast Asian Pharmacogenomics Research Network (SEAPharm). Human Genome Variation volume 8, Article number: 7 (2021).
- Hang Tong, Nga VT Phan, Thanh T. Nguyen, Dinh Nguyen, Nam Sy Vo, Ly Le. Review on Databases and Bioinformatic Approaches on Pharmacogenomics of Adverse Drug Reactions. Pharmgenomics Pers Med. 2021; 14: 61–75.
- With the TCGA PanCanAtlas Immune Response Working Group. The Immune Landscape of Cancer. Cell Immunity, 48(4), 812-830 (2018).
- With the TCGA PanCanAtlas Fusion/Splicing Working Group. Systematic Analysis of Splice-Site-Creating Mutations in Cancer. Cell Reports, 23(1), 270-281 (2018).
- Nam S. Vo, Vinhthuy Phan. Leveraging Known Genomic Variants to Improve Detection of Variants, Especially Close-by Indels. Bioinformatics, 34(17), 2918–2926 (2018).
- Nam S. Vo, Vinhthuy Phan. Exploiting Dependencies of Pairwise-comparison Outcomes to Predict Patterns of Gene Response. Best paper runner-up award, MCBIOS 2014. BMC Bioinformatics, 15(S-11): S2 (2015).
- Vinhthuy Phan, Shanshan Gao, Quang Tran, Nam S. Vo. How Genome Complexity Can Explain the Hardness of Aligning Reads to Genomes. BMC Bioinformatics, 16(S-17): S3 (2015).
- Nam S. Vo, Quang Tran, Nobal Niraula, Vinhthuy Phan. RandAL: A Randomized Approach to Aligning DNA Sequences to Reference Genomes. BMC Genomics, 15(S-5): S2 (2014).
- Duc Tran, Frederick C Harris, Bang Tran, Nam Sy Vo, Hung Nguyen, Tin Nguyen. Single-cell RNA sequencing data imputation using deep neural network. In: Latifi S. (eds) ITNG 2021, Advances in Intelligent Systems and Computing, vol 1346. Springer, Cham.
- Quang Tran, Nam S. Vo, Eric Hicks, Tin Nguyen, Vinhthuy Phan. Analysis of Short-read Aligners using Genome Sequence Complexity. IEEE International Conference on Knowledge and Systems Engineering (KSE), October 2020.
- Bang Tran, Duc Tran, Hung Nguyen, Nam S. Vo, Tin Nguyen. RIA: a novel Regression-based Imputation Approach for single-cell RNA sequencing. IEEE International Conference on Knowledge and Systems Engineering (KSE), October 2019.
- Quang Tran, Shanshan Gao, Nam S. Vo, Vinhthuy Phan. Repeat Complexity of Genomes as a Means to Predict the Performance of Short-read Aligners. International Conference on Bioinformatics and Computational Biology (BICoB), April 2016.
- Vinhthuy Phan, Shanshan Gao, Quang Tran, Nam S. Vo. How Genome Complexity Can Explain the Hardness of Aligning Reads to Genomes. IEEE International Conference on Computational Advances in Bio and Medical Sciences (ICCABS), June 2014.
- Nam S. Vo, Quang Tran, Nobal Niraula, Vinhthuy Phan. A Randomized Algorithm for Aligning DNA Sequences to Reference Genomes. ICCABS, June 2013.
- Nam S. Vo and Vinhthuy Phan. Exploiting Dependencies of Patterns in Gene Expression Analysis using Pairwise Comparisons. International Symposium on Bioinformatics Research and Applications, May 2013.
- Nam S. Vo, Thomas Sutter, Vinhthuy Phan. Inferring Directed-graph Patterns of Gene Responses in Gene Expression Studies with Multiple Treatments. BICoB, March 2013.
- Nam S. Vo, Vinhthuy Phan, Thomas Sutter, Predicting Possible Directed-graph Patterns of Gene Expressions in Studies Involving Multiple Treatments, ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB), October 2012.
- Nam S. Vo and Vinhthuy Phan, Pattern Analysis: A Web-based Tool for Analyzing Response Patterns in Low-replication, Many-treatment Gene Expression Data. ACM-BCB, October 2012.
Others (abstracts, posters):
- Nam S. Vo, Zhenyu Zhang, and Robert L. Grossman. Somatic Variant Detection from Tumor-only Samples. Conference on Intelligent Systems for Molecular Biology (ISMB), July
- Quang Tran, Shanshan Gao, Nam S. Vo, Vinhthuy Phan. A linear model for predicting performance of short-read aligners using genome complexity. UT-ORNL-KBRIN 2015, BMC Bioinformatics, P17 (2015).
- Nam S. Vo, Quang Tran, Vinhthuy Phan. An Integrated Approach for SNP Calling based on Population of Genomes. UT-ORNL-KBRIN 2014, BMC Bioinformatics 15(Suppl 10): P30 (2014).
- Nam S. Vo, Vinthuy Phan. Exploiting the bootstrap method to analyze patterns of gene expression. UT-ORNL-KBRIN 2014, BMC Bioinformatics 15, P19 (2014).
- Nam S. Vo and Vinhthuy Phan. Using Partially Ordered Sets to Represent and Predict True Patterns of Gene Response to Treatments. UT-ORNL-KBRIN 2013, BMC Bioinformatics 14(Suppl 17): A20 (2013).
- Vinhthuy Phan, Nam S. Vo, Thomas R. Sutter. mDAG: A Web-based Tool for Analyzing Microarray Data with Multiple Treatments. UT-ORNL-KBRIN 2011, BMC Bioinformatics 12(Suppl 7): A7 (2011).
- Thach Pham, Son Ho, Quynh Pham, Anh Nguyen et al. Artificial Intelligence powered, Melting-Spectrum PCR (AIMS-PCR) enables massive screening for SARS-CoV-2.
- Journal reviews: Nature Methods, Bioinformatics, Frontiers in Oncology, BMC Bioinformatics, BMC Medical Genomics.
- Conference reviews: RECOMB, RECOMB-CBB, AICoB, BIBM.
- Program committee: IEEE International Conference on Knowledge and Systems Engineering, Genomic Medicine Conference.
- Panel reviews: Vingroup Innovation Foundation (VINIF).
- Invited talks:
- Genomic Big Data: What can we do? National University of Civil Engineering, Viet Nam, 11/2019.
- Mathematical Methods for the Understanding of the Human Genome. International Graduate Summer School in Mathematics, Ha Noi, Viet Nam, 08/2019.
- Mathematical Methods for the Understanding of the Human Genome. VN-USA Joint Mathematical Meeting, Quy Nhon, Viet Nam, 06/2019.
- Predicting Response to Cancer Immunotherapy: Big Data Approaches. Genomic Medicine Conference, Ha Noi, Viet Nam, 06/2019.
- Towards a Software Platform for Big Data in Biomedical Research. Vingroup Institute of Big Data, Vietnam, 12/2018.
- NCI’s Genomic Data Commons: Research and Development, Vinmec Research Institute of Stem Cell and Gene Technology, Viet Nam, 09/2018.
- Genomic Variant Analysis for Computational Immunogenomics, Vinmec Research Institute of Stem Cell and Gene Technology, Viet Nam, 07/2017.
- Other talks:
- Neoantigen Predictions from Splice-creating Mutations. TCGA PanCanAtlas Fusion/Splicing Working Group Teleconference, 10/2017.
- From Genomic Variant Analysis to Computational Immunogenomics. The University of Chicago, USA, 09/2017.
- Genomic Variant Analysis for Cancer Immunogenomics. The New York Genome Center, USA, 09/2017.
- Neoantigen Predictions from InDels, TCGA PanCanAtlas Immune Response Working Group Teleconference, 04/2017.
- Computational Methods for Genomic Variant and Gene Expression Analysis, The University of Texas MD Anderson Cancer Center, USA, 06/2016.
- Oral/poster presentations:
- Leveraging Known Genomic Variants to Improve Variant Detection. ISMB, poster presentation, 07/
- Somatic Variant Detection from Tumor-only Samples. ISMB, poster presentation, 07/
- Improving Variant Calling by Incorporating Known Genetic Variants into Read Alignment, MCBIOS, poster presentation, 03/2015.
- Predicting True Patterns of Gene Response to Treatments in Expression Analysis using Pairwise Comparisons. MCBIOS, selected oral presentation, 03/2014.
- Using Partially Ordered Sets to Represent and Predict True Patterns of Gene Response to Treatments, UT-ORNL-KBRIN Summit, selected oral presentation, 03/2013.
- Predicting Possible Directed-graph Patterns of Gene Expressions in Studies Involving Multiple Treatments, ACM-BCB, poster presentation, 10/2012.
- Pattern Analysis: A Web-based Tool for Analyzing Response Patterns in Low-replication, Many-treatment Gene Expression Data, ACM-BCB, poster presentation, 10/2012.